Coupling Relationship Analysis of Gold Content Using Gaofen-5 (GF-5) Satellite Hyperspectral Remote Sensing Data: A Potential Method in Chahuazhai Gold Mining Area, Qiubei County, SW China

The gold (Au) geochemical anomaly is an important indicator of gold mineralization. While the traditional field geochemical exploration method is time-consuming and expensive, the hyperspectral remote sensing technique serves as a robust technique for the delineation and mapping of hydrothermally altered and weathered mineral deposits. Nonetheless, mineralization element anomaly detection was still seldomly used in previous hyperspectral remote sensing applications in mineralization. This study explored the coupling relationship between Gaofen-5 (GF-5) hyperspectral data and Au geochemical anomalies through several models. The Au geochemical anomalies in the Chahuazhai mining area, Qiubei County, Yunnan Province, SW China, was studied in detail. First, several noise reduction methods including radiometric calibration, Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), Savitzky–Golay filter, and endmember choosing methods including Minimum Noise Fraction (MNF) transformation, matched filtering, and Fast Fourier Transform (FFT) transformation were applied to the Gaofen-5 (GF-5) hyperspectral data processing. The Spectrum-Area (S-A) method was introduced to build an FFT filter to highlight the spectral abnormal characteristics associated with Au geochemical anomaly information. Specifically, the Matched Filtering (MF) technique was applied to the dataset to find the Au geochemical anomaly abundances of endmembers with innovative large-sample learning. Then, Multiple Linear Regression (MLR), Partial Least Squares (PLS) regression, a Back Propagation (BP) network, and Geographically Weighted Regression (GWR) were used to reveal the coupling relationship between the spectra of the processed hyperspectral data and the Au geochemical anomalies. The results show that the GWR analysis has a much higher coefficient of determination, which implies that the Au geochemical anomalies and the spectral information are highly related to spatial locations. GWR works especially well for showing the regional Au geochemical anomaly trend and simulating the Au concentrated areas. The GWR model with application of the S-A method is applicable to the detection of Au geochemical anomalies, which could provide a potential method for Au deposit exploration using GF-5 hyperspectral data.

Kaoline Mapping Using ASTER Satellite Imagery: The Case Study of Kefalos Peninsula, Kos Island

The present work aims to map kaolin occurrences on the Kefalos peninsula, SW Kos Island, Greece, through the elaboration of ASTER satellite imagery. The island of Kos is located on the eastern edge of the South Aegean Active Volcanic Arc (SAAVA) and is characterised by its complex geologic structure. During Plio-Pleistocene, the voluminous eruption of the Kos Plateau Tuff was recorded on Kefalos; the largest quaternary eruption in the Mediterranean. Kaolin is the product of hydrothermal alteration of the Pliocene volcanic rocks with rhyolitic composition. Our study emphasises the usefulness of satellite imagery combined with the Mixture Tuned Matched Filtering (MTMF) technique to detect occurrences of industrial minerals, kaolin-group minerals in this case, either in terms of raw mineral exploitation or by mapping hydrothermal alteration.

Matched Filtering in Massive MU-MIMO Systems

<p>This thesis considers the analysis of matched filtering (MF) processing in massive multi-user multiple-input-multiple-output (MU-MIMO) wireless communication systems. The main focus is the analysis of system performance for combinations of two linear processers, analog maximum ratio combining (MRC) and digital MRC. We consider implementations of these processing techniques both at a single base-station (BS) and in distributed BS layouts. We further consider extremely low complexity distributed variants of MRC for such systems. Since MRC relies on the massive MIMO properties of favourable propagation (FP) and channel hardening, we also present a detailed analysis of FP and channel hardening. This analysis employs modern ray-based models rather than classical channel models as the models are more reliable for the large arrays and higher frequencies envisaged for future systems. The importance of MRC processing is being driven by the emergence of massive MIMO and millimetre wave as strong candidates for next generation wireless communication systems. Massive MIMO explores the spatial dimension by providing significant increases in data rate, link reliability and energy efficiency. However, with a large number of antennas co-located in a fixed physical space, correlation between the elements of antennas may have a negative impact. Distributed systems, where the total number of antennas are divided into different locations, make this problem less serious. Also, linear processing techniques, analog MRC and digital MRC, due to their simplicity and efficiency, are more practical in massive MU-MIMO systems. For these reasons we consider MRC processing in both co-located and distributed scenarios. Although distributed systems reduce the adverse impact of correlation caused by closely-spaced large antenna arrays by dividing the antennas into multiple antenna clusters, the correlation within the cluster still exists. Thus, we extend MRC analysis for massive MIMO to correlated channels. Approximations of expected per-user spectrum efficiency (SE) with correlation effects for massive MIMO systems with analog MRC and digital MRC are derived. Useful insights are given for future system deployments. A convergence analysis of the interference behaviour under different correlation models is presented. Furthermore, a distributed fully cooperative system, where all the received signals are sent to the central processor, offers attractive performance gains but at the cost of high computational complexity at the central node. Thus, we propose four low-complexity, two-stage processors, where only processed signals after local processing (first-stage) are transmitted to the global processing node (second-stage). We present analytical expressions for the expected per user SINR in an uplink distributed MU-MIMO system with two-stage beam-forming. This leads to an approximation of expected per-user SE. The analysis of both millimetre wave and massive MIMO systems requires a strong link to the physical environment and ray-based models are more practical and suitable for such systems. However, it is unclear how the key properties in conventional MIMO systems, such as FP and channel hardening, will behave in a ray-based channel model. In this thesis, remarkably simple and general results are obtained demonstrating that: a) channel hardening may or may nor occur depending on the nature of the channel models; b) FP is guaranteed for all models as long as the ray angles are continuous random variables; c) we also propose a novel system metric, denoted large system potential (LSP) as the ratio of the mean desired signal power to the total mean interference power, where both the numbers of antennas and end-users are growing to infinity at a fixed ratio. We derive simple approximations to LSP and demonstrate that LSP will not normally hold as the mean interference power usually grows logarithmically relative to the mean signal power.</p>

Matched Filtering in Massive MU-MIMO Systems

<p>This thesis considers the analysis of matched filtering (MF) processing in massive multi-user multiple-input-multiple-output (MU-MIMO) wireless communication systems. The main focus is the analysis of system performance for combinations of two linear processers, analog maximum ratio combining (MRC) and digital MRC. We consider implementations of these processing techniques both at a single base-station (BS) and in distributed BS layouts. We further consider extremely low complexity distributed variants of MRC for such systems. Since MRC relies on the massive MIMO properties of favourable propagation (FP) and channel hardening, we also present a detailed analysis of FP and channel hardening. This analysis employs modern ray-based models rather than classical channel models as the models are more reliable for the large arrays and higher frequencies envisaged for future systems. The importance of MRC processing is being driven by the emergence of massive MIMO and millimetre wave as strong candidates for next generation wireless communication systems. Massive MIMO explores the spatial dimension by providing significant increases in data rate, link reliability and energy efficiency. However, with a large number of antennas co-located in a fixed physical space, correlation between the elements of antennas may have a negative impact. Distributed systems, where the total number of antennas are divided into different locations, make this problem less serious. Also, linear processing techniques, analog MRC and digital MRC, due to their simplicity and efficiency, are more practical in massive MU-MIMO systems. For these reasons we consider MRC processing in both co-located and distributed scenarios. Although distributed systems reduce the adverse impact of correlation caused by closely-spaced large antenna arrays by dividing the antennas into multiple antenna clusters, the correlation within the cluster still exists. Thus, we extend MRC analysis for massive MIMO to correlated channels. Approximations of expected per-user spectrum efficiency (SE) with correlation effects for massive MIMO systems with analog MRC and digital MRC are derived. Useful insights are given for future system deployments. A convergence analysis of the interference behaviour under different correlation models is presented. Furthermore, a distributed fully cooperative system, where all the received signals are sent to the central processor, offers attractive performance gains but at the cost of high computational complexity at the central node. Thus, we propose four low-complexity, two-stage processors, where only processed signals after local processing (first-stage) are transmitted to the global processing node (second-stage). We present analytical expressions for the expected per user SINR in an uplink distributed MU-MIMO system with two-stage beam-forming. This leads to an approximation of expected per-user SE. The analysis of both millimetre wave and massive MIMO systems requires a strong link to the physical environment and ray-based models are more practical and suitable for such systems. However, it is unclear how the key properties in conventional MIMO systems, such as FP and channel hardening, will behave in a ray-based channel model. In this thesis, remarkably simple and general results are obtained demonstrating that: a) channel hardening may or may nor occur depending on the nature of the channel models; b) FP is guaranteed for all models as long as the ray angles are continuous random variables; c) we also propose a novel system metric, denoted large system potential (LSP) as the ratio of the mean desired signal power to the total mean interference power, where both the numbers of antennas and end-users are growing to infinity at a fixed ratio. We derive simple approximations to LSP and demonstrate that LSP will not normally hold as the mean interference power usually grows logarithmically relative to the mean signal power.</p>

Real-time Search for Compact Binary Mergers in Advanced LIGO and Virgo's Third Observing Run Using PyCBC Live

The third observing run of Advanced LIGO and Advanced Virgo took place between 2019 April and 2020 March and resulted in dozens of gravitational-wave candidates, many of which are now published as confident detections. A crucial requirement of the third observing run was the rapid identification and public reporting of compact binary mergers, which enabled massive follow-up observation campaigns with electromagnetic and neutrino observatories. PyCBC Live is a low-latency search for compact binary mergers based on frequency-domain matched filtering, which was used during the second and third observing runs, together with other low-latency analyses, to generate these rapid alerts from the data acquired by LIGO and Virgo. This paper describes and evaluates the improvements made to PyCBC Live after the second observing run, which defined its operation and performance during the third observing run.

High SNR Φ-OTDR with Multi-Transverse Modes Heterodyne Matched-Filtering Technology

Phase-sensitive optical time domain reflectometer (Φ-OTDR) has attracted attention in scientific research and industry because of its distributed dynamic linear response to external disturbances. However, the signal-to-noise ratio (SNR) of Φ-OTDR is still a limited factor by the weak Rayleigh Backscattering coefficient. Here, the multi-transverse modes heterodyne matched-filtering technology is proposed to improve the system SNR. The capture efficiency and nonlinear threshold are increased with multiple transverse modes in few-mode fibers; the incident light energy is permitted to be enlarged by a wider probe pulse by using heterodyne matched-filtering without spatial resolution being deteriorated. As far as we know, this is the first time that both multi-transverse modes integration method and digital heterodyne matched filtering method have been used to improve the SNR of Φ-OTDR simultaneously. Experimental results show that the noise floor is reduced by 11.4 dB, while the target signal is kept. We believe that this proposed method will help DAS find important applications in marine acoustic detection and seismic detection.

An Improved PMF-FFT Algorithm Based on Hamming Window

When the rocket uses low-orbit satellite space-based measurement and control, due to the relatively large Doppler shift in relative motion, a spread spectrum system is needed to improve anti-interference; the spread spectrum signal under high dynamic conditions often uses partial matched filtering based on FFT (PMF-FFT) algorithm, but due to the introduction of FFT, this algorithm has serious scallop loss, which affects the system’s capture performance. Through the improved method of adding a Hamming window to the system, theoretical analysis and simulation show that it effectively suppresses scallops. Loss has a certain meaning for the acquisition of spread spectrum signals.